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Valente, A, Sathyendranath S, Brotas V, Groom S, Grant M, Taberner M, Antoine D, Arnone R, Balch WM, Barker K, Barlow R, Belanger S, Berthon JF, Besiktepe S, Brando V, Canuti E, Chavez F, Claustre H, Crout R, Frouin R, Garcia-Soto C, Gibb S, Gould R, Hooker S, Kahru M, Klein H, Kratzer S, Loisel H, McKee D, Mitchell BG, Moisan T, Muller-Karger F, O'Dowd L, Ondrusek M, Poulton AJ, Repecaud M, Smyth T, Sosik HM, Twardowski M, Voss K, Werdell J, Wernand M, Zibordi G.  2016.  A compilation of global bio-optical in situ data for ocean-colour satellite applications. Earth System Science Data. 8:235-252.   10.5194/essd-8-235-2016   AbstractWebsite

A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately. The compiled data are available at doi: 10.1594/PANGAEA.854832 (Valente et al., 2015).

Kahru, M, Jacox MG, Lee Z, Kudela RM, Manzano-Sarabia M, Mitchell BG.  2015.  Optimized multi-satellite merger of primary production estimates in the California Current using inherent optical properties. Journal of Marine Systems. 147:94-102.   10.1016/j.jmarsys.2014.06.003   AbstractWebsite

Building a multi-decadal time series of large-scale estimates of net primary production (NPP) requires merging data from multiple ocean color satellites. The primary product of ocean color sensors is spectral remote sensing reflectance (Rrs). We found significant differences (13-18% median absolute percent error) between Rrs estimates at 443 nm of different satellite sensors. These differences in Rrs are transferred to inherent optical properties and further on to estimates of NPP. We estimated NPP for the California Current region from three ocean color sensors (SeaWiFS, MODIS-Aqua and MERIS) using a regionally optimized absorption based primary production model (Aph-PP) of Lee et al. (2011). Optimization of the Aph-PP model was required for each individual satellite sensor in order to make NPP estimates from different sensors compatible with each other. While the concept of Aph-PP has advantages over traditional chlorophyll-based NPP models, in practical application even the optimized Aph-PP model explained less than 60% of the total variance in NPP which is similar to other NPP algorithms. Uncertainties in satellite Rrs estimates as well as uncertainties in parameters representing phytoplankton depth distribution and physiology are likely to be limiting our current capability to accurately estimate NPP from space. Introducing a generic vertical profile for phytoplankton improved slightly the skill of the Aph-PP model. (C) 2014 Elsevier B.V. All rights reserved.

Kahru, M, Kudela RM, Anderson CR, Manzano-Sarabia M, Mitchell BG.  2014.  Evaluation of satellite retrievals of ocean chlorophyll-a in the California Current. Remote Sensing. 6:8524-8540.   10.3390/rs6098524   AbstractWebsite

Retrievals of ocean surface chlorophyll-a concentration (Chla) by multiple ocean color satellite sensors (SeaWiFS, MODIS-Terra, MODIS-Aqua, MERIS, VIIRS) using standard algorithms were evaluated in the California Current using a large archive of in situ measurements. Over the full range of in situ Chla, all sensors produced a coefficient of determination (R-2) between 0.79 and 0.88 and a median absolute percent error (MdAPE) between 21% and 27%. However, at in situ Chla > 1 mg m(-3), only products from MERIS (both the ESA produced algal_1 and NASA produced chlor_a) maintained reasonable accuracy (R-2 from 0.74 to 0.52 and MdAPE from 23% to 31%, respectively), while the other sensors had R-2 below 0.5 and MdAPE higher than 36%. We show that the low accuracy at medium and high Chla is caused by the poor retrieval of remote sensing reflectance.

Kahru, M, Kudela RM, Manzano-Sarabia M, Mitchell BG.  2012.  Trends in the surface chlorophyll of the California Current: Merging data from multiple ocean color satellites. Deep-Sea Research Part Ii-Topical Studies in Oceanography. 77-80:89-98. Abstract

Standard remote sensing reflectance products from four ocean color sensors (OCTS, SeaWiFS, MODISA, MERIS) and over 10,000 in situ measurements of surface chlorophyll-a (Chl-a) concentration in the California Current were used to create empirical algorithms that are consistent with in situ data as well as between individual sensors. Using these algorithms, a merged multi-sensor time series of the surface Chl-a concentration in California Current region was created. The merged Oil-a time series (November 1996-December 2011) show a significant (P < 0.01) increasing trend off central California and significant (P < 0.01) decreasing trends in the central North Pacific gyre and off southern Baja California. Although this 15-year time series is too short to separate interannual and multidecadal cycles from climate trends, both of these trends are consistent with the predicted effects of global warming. The expected increase in vertical stratification of the water column and the resulting decreased vertical flux of nutrients would lead to lower Chl-a in the gyre but the increased upwelling-favorable winds leading to stronger upwelling off central California or the increased nitrate content of the upwelled water would lead to higher Chl-a in the upwelling region. The decreased Chl-a off southern Baja California resembles the effect of a decreased influence of strong El Nino events. (c) 2012 Elsevier Ltd. All rights reserved.

Murakami, H, Sasaoka K, Hosoda K, Fukushima H, Toratani M, Frouin R, Mitchell BG, Kahru M, Deschamps PY, Clark D, Flora S, Kishino M, Saitoh S, Asanuma I, Tanaka A, Sasaki H, Yokouchi K, Kiyomoto Y, Saito H, Dupouy C, Siripong A, Matsumura S, Ishizaka J.  2006.  Validation of ADEOS-II GLI ocean color products using in-situ observations. Journal of Oceanography. 62:373-393.   10.1007/s10872-006-0062-6   AbstractWebsite

The Global Imager (GLI) aboard the Advanced Earth Observing Satellite-II (ADEOS-II) made global observations from 2 April 2003 to 24 October 2003. In cooperation with several institutes and scientists, we obtained quality controlled match-ups between GLI products and in-situ data, 116 for chlorophyll-a concentration (CHLA), 249 for normalized water-leaving radiance (nLw) at 443 nm, and 201 for aerosol optical thickness at 865 nm (Tau_865) and Angstrom exponent between 520 and 865 nm (Angstrom). We evaluated the GLI ocean color products and investigated the causes of errors using the match-ups. The median absolute percentage differences (MedPD) between GLI and in-situ data were 14.1-35.7% for nLws at 380-565 nm 52.5-74.8% nLws at 625-680 nm, 47.6% for Tau_865, 46.2% for Angstrom, and 46.6% for CHLA, values that are comparable to the ocean-color products of other sensors. We found that some errors in GLI products are correlated with observational conditions; nLw values were underestimated when nLw at 680 nm was high, CHLA was underestimated in absorptive aerosol conditions, and Tau_865 was overestimated in sunglint regions. The error correlations indicate that we need to improve the retrievals of the optical properties of absorptive aerosols and seawater and sea surface reflection for further applications, including coastal monitoring and the combined use of products from multiple sensors.